The region classifier \(\mathcal {G}\)  predicts the target region, i.e., \(g = \mathcal {G}(I, Q)\) .
We design this module as a model that, given a question and a set of candidate regions, outputs the region that is most relevant to the question.
This problem setup is similar to that of the Referring Expression Comprehension (RE Comprehension) [1]}.
Therefore, we used a fine-tuned version of UNITER grounding model [2]}, which has achieved high performance in RE Comprehension task.
This module returns “valid” if the predicted region is sufficiently close to the target region.
We calculated the IoBB (Intersection over Bounding Box) between the predicted region and the target region and considered two regions sufficiently close if the value was greater than 0.4.
